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1. Technical Field
This invention relates generally to digital coding systems. More particularly, this invention relates to digital speech coding systems having noise suppression.
2. Related Art
Telecommunication systems include both landline and wireless radio systems. Wireless telecommunication systems use radio frequency (RF) communication. Currently, the frequencies available for wireless systems are centered in frequency ranges around 900 MHz and 1900 MHz. The expanding popularity of wireless communication devices, such as cellular telephones is increasing the RF traffic in these frequency ranges. Reduced bandwidth communication would permit more data and voice transmissions in these frequency ranges, enabling the wireless system to allocate resources to a larger number of users.
Wireless systems may transmit digital or analog data. Digital transmission, however, has greater noise immunity and reliability than analog transmission. Digital transmission also provides more compact equipment and the ability to implement sophisticated signal processing functions. In the digital transmission of speech signals, an analog-to-digital converter samples an analog speech waveform. The digitally converted waveform is compressed (encoded) for transmission. The encoded signal is received and decompressed (decoded). After digital-to-analog conversion, the reconstructed speech is played in an earpiece, loudspeaker, or the like.
The analog-to-digital converter uses a large number of bits to represent the analog speech waveform. This larger number of bits creates a relatively large bandwidth. Speech compression reduces the number of bits that represent the speech signal, thus reducing the bandwidth needed for transmission. However, speech compression may result in degradation of the quality of decompressed speech. In general, a higher bit rate results in a higher quality, while a lower bit rate results in a lower quality.
Modern speech compression techniques (coding techniques) produce decompressed speech of relatively high quality at relatively low bit rates. One coding technique attempts to represent the perceptually important features of the speech signal without preserving the actual speech waveform. Another coding technique, a variable-bit rate encoder, varies the degree of speech compression depending on the part of the speech signal being compressed. Typically, perceptually important parts of speech (e.g., voiced speech, plosives, or voiced onsets) are coded with a higher number of bits. Less important parts of speech (e.g., unvoiced parts or silence between words) are coded with a lower number of bits. The resulting average of the varying bit rates can be relatively lower than a fixed bit rate providing decompressed speech of similar quality. These speech compression techniques lower the amount of bandwidth required to digitally transmit a speech signal.
Noise suppression improves the quality of the reconstructed voice signal and helps variable-rate speech encoders distinguish voice parts from noise parts. Noise suppression also helps low bit-rate speech encoders produce higher quality output by improving the perceptual speech quality. Some filtering techniques remove specific noises. However, most noise suppression techniques remove noise by spectral subtraction methods in the frequency domain. A voice activity detector (VAD) determines in the time-domain whether a frame of the signal includes speech or noise. The noise frames are analyzed in the frequency-domain to determine characteristics of the noise signal. From these characteristics, the spectra from noise frames are subtracted from the spectra of the speech frames, providing a “clean” speech signal in the speech frames.
Frequency-domain noise suppression techniques reduce some background noise in the speech frames. However, the frequency-domain techniques introduce significant speech distortion if the background noise is excessively suppressed. Additionally, the spectral subtraction method assumes noise and speech signals are in the same phase, which actually is not real. The VAD may not adequately identify all the noise frames, especially when the background noise is changing rapidly from frame to frame. The VAD also may show a noise spike as a voice frame. The frequency-domain noise suppression techniques may produce a relatively unnatural sound overall, especially when the background noise is excessively suppressed. Accordingly, there is a need for a noise suppression system that accurately reduces the background noise in a speech coding system.